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Minimum‐data analysis of ecosystem service supply in semi‐subsistence agricultural systems

Antle and Valdivia (2006, Australian Journal of Agricultural and Resource Economics 50, 1–15) proposed a minimum‐data (MD) approach to simulate ecosystem service supply curves that can be implemented using readily available secondary data and validated the approach in a case study of soil carbon sequestration in a monoculture wheat system. However, many applications of the MD approach are in developing countries where semi‐subsistence systems with multiple production activities are being used and data availability is limited. This paper discusses how MD analysis can be applied to more complex production systems such as semi‐subsistence systems with multiple production activities and presents validation analysis for studies of soil carbon sequestration in semi‐subsistence farming systems in Kenya and Senegal. Results from these two studies confirm that ecosystem service supply curves based on the MD approach are close approximations to the curves derived from highly detailed data and models and are therefore sufficiently accurate and robust to be used to support policy decision making.
- Wageningen University & Research Netherlands
- Oregon State University United States
- Montana State University System United States
- Montana State University United States
- Montclair State University United States
Leerstoelgroep Ontwikkelingseconomie, model, design, sustainability, carbon sequestration, payments, Leerstoelgroep Landdynamiek, kenya, policies, efficiency, ecosystem services, Kenya, minimum data model, semi-subsistence agriculture, Senegal, Agribusiness, Demand and Price Analysis,
Leerstoelgroep Ontwikkelingseconomie, model, design, sustainability, carbon sequestration, payments, Leerstoelgroep Landdynamiek, kenya, policies, efficiency, ecosystem services, Kenya, minimum data model, semi-subsistence agriculture, Senegal, Agribusiness, Demand and Price Analysis,
citations This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).28 popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.Top 10% influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).Top 10% impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.Top 10%
